Netflix Analytics Engineer vs Data Scientist

Spotify Jgfklo
Jul 28, 2018 11 Comments

I’ve been looking at jobs in the science and analytics group at Netflix and am curious about the data science and analytics engineering roles. I see quite a bit of overlap for some of the job descriptions.

I know there are tons of different data science jobs (machine learning, experimentation, etc) in the group but, in general, how different are the analytics engineer and data scientist roles?

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TOP 11 Comments
  • Netflix RKrN67
    There’s a broad spectrum of AE in terms of skillsets. One can be strong on the DE, data analysis, stats, ml, or visualization/ dashboarding side.
    Jul 29, 20181
  • Facebook / Eng
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    FacebookEng

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    I started at Netflix two months ago as a DE. AE seems a bit more technical and coding oriented than DS. DS seems more ML and statistic intensive.

    Coming from FB where AE doesn’t exist, it’s been kinda hard for me to see where my work as a DE ends and the AE works starts.
    Jul 28, 20185
    • LinkedIn Pretakalpa
      Isn't FB's Data engineer role more towards writing SQLs while Analytics Engg is like ML Engg?
      Jul 28, 2018
    • Facebook / Eng
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      Netflix has a data engineering role too which is much more than writing SQLs. It also has a bunch of ML components to it.
      Analytics Eng and Data Eng have more overlap at Netflix than Analytics Eng and Data Scientist. At least in my first months here it seems that way.
      Jul 28, 2018
    • LinkedIn Pretakalpa
      Thanks for your reply. So were you a DE at FB previously? (I am myself in a DEish role and looking to transition into more coding +ML based role like Nflx Analytics Engg)
      Jul 28, 2018
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      FacebookEng

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      Yeah I was a technical DE at FB who built frameworks and infra.
      Jul 28, 2018
    • Spotify Jgfklo
      OP
      Thanks for sharing!
      Jul 29, 2018
  • Netflix login
    The differences between the two at Netflix are not within the skill set, rather in expectation of the roles. AE is expected to solve business problems using any means and methods in the most efficient ways, whether it is through ML, dashboarding, automation, ab test, adhoc analyses or ETL. DS are expected to gear more toward research side of the house; they are not expected to solve pressing problems like the AE's.
    Jul 29, 20181
    • Spotify Jgfklo
      OP
      This is super super helpful! Are you in any of these roles currently?
      Jul 29, 2018
  • LinkedIn tVfy86
    +1 to replies above. On the one end you have data engineers; on the other end you have data scientists, and an AE floats in between depending on the need of the business / stakeholders. At least, this is how a former AE/current DE at Netflix described it to me.
    Jul 31, 20180

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